李国法，博士，中国科协青年托举人才。1986年11月生，河南鹤壁人。2010年7月本科毕业于北京理工大学机械与车辆学院，2016年6月博士毕业于清华大学汽车工程系，美国University of Michigan联合培养博士。2019年9月至2020年9月加拿大University of Waterloo访问学者。研究方向主要包括智能网联汽车中的环境感知、驾驶行为、决策控制。先后主持国家自然科学基金2项，省部级项目2项。发表论文60余篇，其中，7篇入选ESI高被引论文，参编英文专著1部、中文专著2部，获国家发明专利授权8项。荣获第六届中国科协优秀科技论文、Automotive Innovation期刊2020年度Best Paper、IFAC CPHS 2020的Best Student Paper、NSK机械工学优秀论文奖、中国汽车工程学会优秀青年工程师等荣誉。目前担任IEEE Sensors Journal的Associate Editor，《中国公路学报》青年编委，IEEE Intelligent Transportation Systems Magazine和Automotive Innovation的Lead Guest Editor，中国汽车工程学会青年工作委员会委员，中国交通运输协会青科委委员。

邮箱：liguofa@cqu.edu.cn; hanshan198@gmail.com

教育经历：

2012.08 – 2013.08，美国University of Michigan，UMTRI，Mechanical Engineering，联合培养博士

2010.09 – 2016.06，清华大学，汽车工程系，机械工程，博士

2006.09 – 2010.07，北京理工大学，机械与车辆学院，车辆工程，学士

工作经历：

2022.10 – 至今，重庆大学，机械与运载工程学院

2016.07 – 2022.09，深圳大学，机电与控制工程学院

主要研究方向：

智能汽车中的：（1）环境感知；（2）驾驶行为；（3）决策控制

主持科研项目：

1.       国家自然科学基金面上项目，融合知识迁移和险态评估的驾驶决策研究，52272421，主持

2.       国家自然科学基金青年基金，高速工况下融合模式转移和操控特性的驾驶风格评测方法研究，51805332，主持（已结题，A+）

3.       中国科协青年人才托举项目，拟人化智能驾驶行为与决策，主持（已结题）

4.       广东省自然科学基金，考虑频度和强度特性的驾驶激进度评测方法研究，2018A030310532，主持（已结题）

5.       国家重点实验室开放基金，驾驶风格量化评测在人-车-路闭环中的多维解析研究，KF1801，主持（已结题）

6.       深圳市面上项目，融合多源异构信息和驾驶风格偏好的智能驾驶决策研究，JCYJ20190808142613246，主持

7.       深圳市稳定支持面上项目（A类），基于异类传感器信息融合的多目标检测与跟踪研究，20200803015912001，主持

主要学术论文：

[1]   G. Li, W. Lai, X. Qu*, “Pedestrian detection based on light perception fusion of visible and thermal images,” Optics & Laser Technology, vol. 156, 108466, Dec. 2022.

[2]   G. Li, X. Chen, M. Li, et al., “One-shot multi-object tracking using CNN-based networks with spatial-channel attention mechanism,” Optics & Laser Technology, vol. 153, 108267, Sep. 2022.

[3]   G. Li, Z. Ji, S. Li, X. Luo, X. Qu*, “Driver Behavioral Cloning for Route Following in Autonomous Vehicles Using Task Knowledge Distillation,” IEEE Transactions on Intelligent Vehicles, early access, Aug. 2022, doi: 10.1109/TIV.2022.3198678.

[4]   G. Li, Z. Ji, X. Qu*, “Stepwise Domain Adaptation (SDA) for Object Detection in Autonomous Vehicles Using an Adaptive CenterNet,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 10, pp. 17729–17743, Oct. 2022.

[5]   W. Li, R. Tan, Y. Xing, G. Li, S. Li, et al., “A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks,” Scientific Data, vol. 9, 481, Aug. 2022.

[6]   G. Li, Z. Ji, X. Qu*, R. Zhou, D. Cao, “Cross-Domain Object Detection for Autonomous Driving: A Stepwise Domain Adaptative YOLO Approach,” IEEE Transactions on Intelligent Vehicles, vol. 7, no. 3, pp. 603–615, Sep. 2022.

[7]   G. Li, D. Ouyang, Y. Yuan, et al., “An EEG Data Processing Approach for Emotion Recognition,” IEEE Sensors Journal, vol. 22, no. 11, pp. 10751–10763, Jun. 2022.

[8]   G. Li, Y. Yang, S. Li, X. Qu*, N. Lyu, S.E. Li, “Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness,” Transportation Research Part C: Emerging Technologies, vol. 134, 103452, Jan. 2022.

[9]   Y. Chen, G. Li*, S. Li, W. Wang, S.E. Li, B. Cheng, “Exploring Behavioral Patterns of Lane Change Maneuvers for Human-Like Autonomous Driving,” IEEE Transactions on Intelligent Transportation Systems, Nov. 2021, DOI: 10.1109/TITS.2021.3127491.

[10]  G. Li, Y. Lin, X. Qu*, “An infrared and visible image fusion method based on multi-scale transformation and norm optimization”, Information Fusion, vol. 71, pp. 109–129, 2021. (ESI高被引论文)

[11]  G. Li, Y. Chen, D. Cao, X. Qu*, B. Cheng, K. Li, “Extraction of descriptive driving patterns from driving data using unsupervised algorithms”, Mechanical Systems and Signal Processing, vol. 156, 107589, 2021. (ESI高被引论文)

[12]  G. Li, Y. Yang, T. Zhang, X. Qu*, D. Cao, B. Cheng, K. Li, “Risk assessment based collision avoidance decision-making for autonomous vehicles in multi-scenarios”, Transportation Research Part C: Emerging Technologies, vol. 122, 102820, 2021. (ESI高被引论文)

[13]  G. Li, Y. Yang, X. Qu*, D. Cao, K. Li, “A deep learning based image enhancement approach for autonomous driving at night”, Knowledge-Based Systems, vol. 213, 106617, 2021. (ESI高被引论文)

[14]  G. Li, Y. Yang, X. Qu*, “Deep learning approaches on pedestrian detection in hazy weather”, IEEE Transactions on Industrial Electronics, vol. 67, no. 10, pp. 8889–8899, Oct. 2020. (ESI高被引论文)

[15]  G. Li, W. Lai, X. Sui, X. Li, X. Qu*, T. Zhang, Y. Li, “Influence of traffic congestion on driver behavior in post-congestion driving”, Accident Analysis and Prevention, vol. 141, 105508, 2020. (ESI高被引论文)

[16]  G. Li, Y. Wang, F. Zhu, X. Sui, N. Wang, X. Qu*, P. Green, “Drivers’ visual scanning behavior at signalized and unsignalized intersections: A naturalistic driving study in China”, Journal of Safety Research, vol. 71, pp. 219–229, 2019. (ESI高被引论文，热点论文)

[17]  G. Li, S. E. Li^*, R. Zou, Y. Liao, B. Cheng, “Detection of road traffic participants using cost-effective arrayed ultrasonic sensors in low-speed traffic situations,” Mechanical Systems and Signal Processing, vol. 132, pp. 535–545, 2019.

[18]  S. E. Li¹, G. Li^1,*, J. Yu, C. Liu, B. Cheng, J. Wang, K. Li, “Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles,” Mechanical Systems and Signal Processing, vol. 98, pp. 173–189, 2018.

[19]  G. Li, S. E. Li*, B. Cheng, P. Green, “Estimation of driving style in naturalistic highway traffic using maneuver transition probabilities,” Transportation Research Part C: Emerging Technologies, vol. 74, pp. 113–125, 2017.

[20]  G. Li, W. Yan, S. Li, X. Qu*, D. Cao, “A temporal-spatial deep learning approach for driver distraction detection based on EEG signals”, IEEE Transactions on Automation Science and Engineering, 2021, DOI: 10.1109/TASE.2021.3088897.

[21]  G. Li, L. Yang, S. Li, X. Luo, X. Qu*, P. Green, “Human-like decision-making of artificial drivers in intelligent transportation systems: an end-to-end driving behavior prediction approach”, IEEE Intelligent Transportation Systems Magazine, Jun. 2021, DOI: 10.1109/MITS.2021.3085986.

[22]  G. Li, S. Lin, S. Li, X. Qu, “Learning automated driving in complex intersection scenarios based on camera sensors: A deep reinforcement learning approach,” IEEE Sensors Journal, vol. 22, no. 5, pp. 4687–4696, 2022.

[23]  D. Zhai, Y. Pan, P. Li, G. Li*, “Estimating the vigilance of high-speed rail drivers using a stacking ensemble learning method”, IEEE Sensors Journal, May. 2021, DOI: 10.1109/JSEN.2021.3077021.

[24]  G. Li, S. Li, S. Li, X. Qu*, “Continuous Decision-Making for Autonomous Driving at Intersections Using Deep Deterministic Policy Gradient”, IET Intelligent Transport Systems, 2021, DOI: 10.1049/itr2.12107.

[25]  G. Li, Z. Ji, Y. Chang, S. Li, X. Qu*, D. Cao, “ML-ANet: A Transfer Learning Approach Using Adaptation Network for Multi-label Image Classification in Autonomous Driving”, Chinese Journal of Mechanical Engineering, vol. 34, Article number: 78, Aug. 2021.

[26]  Y. Qin, Z. Zhao, Z. Wang, G. Li*, “Study of longitudinal-vertical dynamics for in-wheel motor driven electric vehicles”, Automotive Innovation, vol. 4, pp. 227–237, 2021.

[27]  G. Li, S. Li, S. Li*, Y. Yang, D. Cao, X. Qu, “Deep reinforcement learning enabled decision-making for autonomous driving at intersections”, Automotive Innovation, vol. 3, pp. 374–385, 2020. (中国科协优秀科技论文，Automotive Innovation 2020年度 Best Paper Award)

[28]  Q. Wen, Z. Luo, R. Chen, Y. Yang, G. Li*, “Deep Learning Approaches on Defect Detection in High Resolution Aerial Images of Insulators,” Sensors, vol. 21, no. 4, Article number: 1033, Feb. 2021. (Editor’s Choice Article)

[29]  G. Li, H. Xie, W. Yan, Y. Chang, X. Qu*, “Detection of road objects with small appearance in images for autonomous driving in various traffic situations using a deep learning based approach,” IEEE Access, vol. 8, pp. 211164–211172, Nov. 2020.

[30]  G. Li, Y. Liao*, Q. Guo, C. Shen, W. Lai, “Traffic crash characteristics in Shenzhen, China from 2014 to 2016”, International Journal of Environmental Research and Public Health, vol. 18, 1176, 2021.

[31]  G. Li, W. Lai, X. Qu*, “Association between crash attributes and drivers’ crash involvement: a study based on police-reported crash data”, International Journal of Environmental Research and Public Health, vol. 17, 9020, 2020.

[32]  G. Li, S. E. Li*, and B. Cheng, “Field operational test of advanced driver assistance systems in typical Chinese road conditions: The influence of driver gender, age and aggression,” International Journal of Automotive Technology, vol. 16, no. 5, pp. 739–750, 2015.

[33]  G. Li, W. Wang, S. Li, B. Cheng*, P. Green, “Effectiveness of flashing brake and hazard systems in avoiding rear-end crashes,” Advances in Mechanical Engineering, vol. 2014, pp. 1–12, 2014.

[34]  S. Li¹, G. Li¹, Y. Cheng, B. Ran*, “Urban arterial traffic status detection using cellular data without cellphone GPS information”, Transportation Research Part C: Emerging Technologies, vol. 114, pp. 446–462, 2020.

[35]  J. Duan, R. Li, L. Hou, W. Wang*, G. Li*, S.E. Li, B. Cheng, H. Gao, “Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts,” Accident Analysis & Prevention, vol. 108, pp. 74–82, 2017.

[36]  李国法，陈耀昱，吕辰，陶达，曹东璞，成波. “智能汽车决策中的驾驶行为语义解析关键技术”, 汽车安全与节能学报，10(4), 391-412, 2019.

[37]  李国法，赖伟鉴，廖源，王文军*，成波. “邻车切入工况下前撞预警系统的驾驶人依赖特性”, 汽车安全与节能学报, 11(1), 36-43, 2020.

[38]  G. Li, Y. Wang, “Surface transportation”, in S.N. Samman (ed.), Human Factors and Ergonomics for the Gulf Cooperation Council: Processes, Technologies, and Practices, CRC Press, pp.191-207, 2018.

[39]  G. Li, F. Zhu, T. Zhang, Y. Wang, S. He, X. Qu. “Evaluation of three in-vehicle interactions from drivers’ driving performance and eye movement behavior”. In Proceedings of the 21th -, pp. 2086-2091, Hawaii, USA, 2018.

[40]  G. Li, S.E. Li, L. Jia, W. Wang, B. Cheng, F. Chen. “Driving maneuvers analysis using naturalistic highway driving data”. In Proceedings of the 18th IEEE International Conference on Intelligent Transportation Systems (ITSC), pp. 1761-1766, Las Palmas, Spain, 2015.

[41]  G. Li, S.E. Li, Y. Liao, W. Wang, B. Cheng, F. Chen. “Lane change maneuver recognition via vehicle state and driver operation signals—Results from naturalistic driving data”. In Proceedings of the 2015 IEEE Intelligent Vehicles Symposium (IV), pp. 865-870, Seoul, Korea, 2015.

[42]  Z. Sun, Y. Liu*, J. Wang, G. Li, C. Anil, K. Li, D. Cao, “Applications of Game Theory in Vehicular Networks: A Survey,” IEEE Communications Surveys and Tutorials, vol. 23, no. 4, pp. 2660–2710, Aug. 2021.

[43]  W. Li, Y. Cui, Y. Ma, X. Chen, G. Li, G. Zeng, G. Guo, D. Cao, “A Spontaneous Driver Emotion Facial Expression (DEFE) Dataset for Intelligent Vehicles: Emotions Triggered by Video-audio Clips in Driving Scenarios”, IEEE Transactions on Affective Computing, 2021, DOI: 10.1109/TAFFC.2021.3063387.

[44]  R. Zeng, Y. Kang*, J. Yang, Z. Wang, G. Li, D. Cao, “Learning-based Terrain Identification with Proprioceptive Sensors for Mobile Robots”, IEEE Transactions on Industrial Electronics, vol. 68, no. 9, pp. 8433–8443, 2020.

[45]  M. Li, H. Cao, G. Li, X. Song, S. Zhao, Y. Chen, D. Cao, “A Two-Layer Potential-Field-Driven Model Predictive Shared Control towards Driver-Automation Cooperation”, IEEE Transactions on Intelligent Transportation Systems, 2021, DOI: 10.1109/TITS.2020.3044666

[46]  J. Xie, K. Hu, G. Li, “CNN-based driving maneuver classification via Multi-sliding window fusion”, Expert Systems with Applications, vol. 169, 114442, 2021.

[47]  L. Yuan, S.E. Li*, W. Wang, Y. Wang, G. Li, B. Cheng, “Detection of driver cognitive distraction: A comparison study of stop-controlled intersection and speed-limited highway”, IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 6, pp. 1628–1637, 2016.

[48]  Q. Li, Z. Wang, W. Wang, C. Zeng, G. Li, Q. Yuan, B. Cheng, “An Adaptive Time Budget Adjustment Strategy Based on a Take-Over Performance Model for Passive Fatigue,” IEEE Transactions on Human-Machine Systems, Nov. 2021, DOI: 10.1109/THMS.2021.3121665

[49]  T. Zhang, W. Zeng, Y. Zhang, D. Tao, G. Li, X., Qu*, “What drives people to use automated vehicles? A meta-analytic review,” Accident Analysis & Prevention, vol. 159, 106270, 2021.

[50]  L. Hou, J. Duan, W. Wang, R. Li, G. Li, B. Cheng, “Drivers’ Braking Behaviors in Different Motion Patterns of Vehicle-Bicycle Conflicts,” Journal of Advanced Transportation, vol. 2019, 4023970, 2019.

[51]  J. Duan, R. Li, L. Hou, W. Wang*, G. Li*, S.E. Li, B. Cheng, H. Gao, “Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts,” Accident Analysis & Prevention, vol. 108, pp. 74–82, 2017.

[52]  J. Zhang, G. Li, Z. Deng, H. Yu, J.P. Huissoon, D. Cao, “Interaction-Aware Cut-in Behavior Prediction and Risk Assessment for Autonomous Driving,” in: Proceedings of the 2020 IFAC, pp. 656-663, 2020. (Best Student Paper Award)

[53]  H. Liu, C. Zhang, C. Xu, G. Li, “KENet: Distilling Convolutional Networks via Knowledge Enhancement,” in: Proceedings of the 2020 IFAC, pp. 385-390, 2020.

[54]  Y. Cui, Y. Ma, W. Li, N. Bian, G. Li, D. Cao, “Multi-EmoNet: A Novel Multi-Task Neural Network for Driver Emotion Recognition,” in: Proceedings of the 2020 IFAC, pp. 650-655, 2020.

[55]  Y. Zhu, Y. Wang, G. Li, X. Guo, “Recognizing and Releasng Drivers' Negative Emotions by Using Music: Evidence from Driver Anger,” in: Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications Adjunct (AutoUI), pp. 173-178, Oct. 24, 2016.

主要专利：

(1)    李国法; 颜伟荃; 赖伟鉴; 陈耀昱; 杨一帆; 李盛龙; 谢恒; 李晓航 ; 一种检测驾驶员分心的方法及装置, 2021-01-29, 中国, ZL 201910707858.4

(2)    李国法; 杨一帆; 李盛龙; 赖伟鉴; 陈耀昱 ; 一种驾驶行为危险度的监测方法及装置, 2021-02-12, 中国, ZL 201911099408.8

(3)    李国法; 朱方平; 杨一帆; 赖伟鉴; 陈耀昱; 谢恒; 李盛龙; 李晓航 ; 一种驾驶风格识别方法及装置, 2021-08-24, 中国, ZL 201910565788.3

(4)    李国法; 陈耀昱; 赖伟鉴; 杨一帆; 李晓航; 林勇杰; 陈昕; 时间序列数据组成模式的提取方法、装置及终端设备, 2022-07-05, 中国, ZL 201911106309.8

(5)    李国法; 杨一帆; 赖伟鉴; 朱方平; 陈耀昱; 曲行达; 一种基于卷积神经网络的道路目标检测方法及装置, 2022-05-03, 中国, ZL 201910931498.6

(6)    李升波; 成波; 李国法; 俞佳莹; 王文军; 段京良; 王建强; 李克强; 基于驾驶模式转移概率的驾驶风格估计方法, 2019-04-05, 中国, ZL 201610391483.1

(7)    成波; 李升波; 李国法;王文军; 贾丽娟; 廖源; 李仁杰; 一种驾驶行为危险度的监测评估方法, 2017-01-25, 中国, ZL 201410777017.8

(8)    李升波; 成波; 徐少兵; 郭强强; 王文军; 李国法; 李仁杰; 忻隆; 一种基于伪谱法的车辆节能加速方式的优化方法, 2017-02-01, 中国, ZL 201410809301.9

(9)    李升波; 成波; 俞佳莹; 李克强; 罗禹贡; 邹若冰; 李国法; 赵国伟; 基于超声波传感器阵列的物体跟踪方法, 2018-11-13, 中国, ZL 201610390557.X

(10) 李升波; 成波; 李仁杰; 王文军; 贾丽娟; 张超飞; 李国法; 廖源; 基于车辆踏板和跟车行为的驾驶员疲劳检测方法, 2019-01-29, 中国, ZL 201610390463.2